What does k-means centroid chart in rapid miner actually mean (in layman's terms)?
Could anyone explain to me what does the centroid chart of k-means in Rapid Miner exactly mean? I know this chart visualizes the centroid values of each feature with respect to the cluster but I need some more expert explanations from experts.
for example, I have questions like, why the "AGE" feature from cluster 0 have positive centroid and cluster 1 have negative centroid?
Thanks in advance for your time :)
Image Source = https://optimalbi.com/wp-content/uploads/2019/06/RapidMiner_Graph-1024x588.png
You can see the essential details of each cluster.
The Centroid Chart shows the values for the cluster centroids in a parallel chart.
You can see:
the size of each cluster
the centroid values of the features within each cluster
for example, I have questions like, why the "AGE" feature from cluster 0 have positive centroid and cluster 1 have negative centroid?
Well, inside each cluster you have some samples and these samples are characterized by some features like Age. So this means that the average value of the Age features of the samples that belong to Cluster 1 is -0.2.
- How do I initialize weights in PyTorch?
- Pytorch GRU error RuntimeError : size mismatch, m1: [1600 x 3], m2: [50 x 20]
- 'super' object has no attribute '__sklearn_tags__'
- What's the major difference between glove and word2vec?
- How to use a Dense layer with an input that has a dynamically sized dimension?
- Optuna Hyperband Algorithm Not Following Expected Model Training Scheme
- What is the difference between Google Cloud Vision API and Mobile Vision?
- How to process requests from multiiple users using ML model and FastAPI?
- Keras ValueError: The layer sequential has never been called and thus has no defined output
- Deep-Learning Nan loss reasons
- Databricks MLFlow and MetaFlow integration
- TypeError: '_IncompatibleKeys' object is not callable
- Does it make sense to use Conda + Poetry?
- Does pytorch CNN care about image size?
- "Found input variables with inconsistent numbers of samples" Have I done something wrong during the train_test_split?
- Feature Selection in PySpark
- tidymodels workflow errors when trying to use workflow_map()
- Integrating numerical/physical data for CNN image classification
- pytorch torchvision.datasets.ImageFolder FileNotFoundError: Found no valid file for the classes .ipynb_checkpoints
- How do I apply one hot encoding on a pandas dataframe with both categorical and numerical features?
- ValueError: could not convert string to float: 'N/'
- Holdout validation set- hyperparameter tuning
- NotFittedError: This DecisionTreeClassifier instance is not fitted yet
- Principal component analysis
- Simple explanation of PCA to reduce dimensionality of dataset
- Dimensionality Reduction – PCA explanation
- PCA after k-means clustering of multidimensional data
- Machine Learning Prediction Project: Getting "ValueError" After Submitting the Prediction Form in the Flask App on Localhost
- How to find the indexes of the first $n$ maximum values of a tensor?
- joblib.load __main__ AttributeError